January 2018
Beginner to intermediate
284 pages
8h 35m
English
Content preview from Deep Learning Essentials
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Advantages of distributed representation
There are many advantages of using distributed word vectors for NLP problems. With the subtle semantic relationships being captured, there is great potential in improving many existing NLP applications, such as machine translation, information retrieval, and question answering system. Some obvious advantages are:
- Capturing local co-occurrence statistics
- Produces state-of-the-art linear semantic relationships
- Efficient use of statistics
- Can train on (comparably) little data and gigantic data
- Fast, only non-zero counts matter
- Good performance with small (100-300) dimension vectors that are important for downstream tasks
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